Update README.md

README.md

@@ -1,3 +1,100 @@
 ---
-license: mit
+license: apache-2.0
+tags:
+- segmentation
+size_categories:
+- 10K<n<100K
 ---
+# CHIP Dataset - Segmentation Training Guide
+
+## Overview
+This dataset is designed for training segmentation models, specifically for human/CHIP segmentation tasks using YOLO models.
+
+## Dataset Structure
+After extracting `CHIP_dataset.zip`, the directory structure should include:
+- `train/` and `valid/` folders with images
+- `data.yaml` configuration file for YOLO training
+
+## Prerequisites
+- Python environment
+- GPU with CUDA support (recommended)
+
+## Installation
+```bash
+pip install ultralytics tqdm
+```
+
+## Download and Extract Dataset
+```bash
+# Download dataset
+wget https://huggingface.co/datasets/OSAS-AI/CHIP-Segmentation/resolve/main/CHIP_dataset.zip
+
+# Extract
+from zipfile import ZipFile
+from tqdm import tqdm
+import os
+
+zip_path = "CHIP_dataset.zip"
+extract_dir = "."
+os.makedirs(extract_dir, exist_ok=True)
+
+with ZipFile(zip_path, "r") as zip_ref:
+    members = zip_ref.infolist()
+    for member in tqdm(members, desc="Extracting", unit="file"):
+        zip_ref.extract(member, extract_dir)
+
+print(f"Extracted to: {extract_dir}")
+```
+
+## Download Pre-trained Model
+```bash
+wget https://huggingface.co/Ultralytics/YOLO26/resolve/main/yolo26s-seg.pt
+```
+
+## Training
+```python
+from ultralytics import YOLO
+
+# Load model
+model = YOLO('yolo26s-seg.pt')  # small variant – good balance
+
+# Train
+results = model.train(
+    data='data.yaml',
+    epochs=300,
+    imgsz=640,
+    batch=32,  # reduce if OOM
+    device="0,1",  # adjust for your GPUs
+    workers=8,
+    project='../runs/train',
+    name='human_segmentation',
+    exist_ok=False,
+    patience=15,
+    save=True,
+    val=True,
+    plots=True
+)
+```
+
+## Key Training Parameters
+- **Model**: YOLOv26s-seg (segmentation)
+- **Image Size**: 640x640
+- **Epochs**: 300
+- **Batch Size**: 32 (adjust based on VRAM)
+- **Multi-GPU**: Supports `device="0,1"`
+
+## Inference / Usage
+After training, the best model will be saved in `runs/train/human_segmentation/weights/best.pt`
+
+```python
+model = YOLO('path/to/best.pt')
+results = model('path/to/image.jpg')
+```
+
+## Dataset on Hugging Face
+[CHIP-Segmentation](https://huggingface.co/datasets/OSAS-AI/CHIP-Segmentation)
+
+For more details, refer to [Ultralytics YOLO documentation](https://docs.ultralytics.com/).
+
+
+You can copy the entire block above and save it as `README.md`. Let me know if you want any changes!